Many current quality evaluation models were designed to produce a single estimate of perceived quality for a video sequence coded at relatively high rates. These metrics perform a multi-channel decomposition to simulate the processes of the Human Visual System (HVS), followed by a distortion pooling stage that collapses the channels over frequency, time and space. Estimating quality at short intervals over the length of a video sequence, however, may be more useful for long video sequences than a single estimate, particularly in such applications as two pass video coding and video quality monitoring. This paper presents an objective metric designed to perform this task on video sequences coded at low bit rates. The metric implements a wavelet transform-based model of the human visual system and a method of temporal error pooling suited to continuous estimation of perceived quality. A time series distance metric based on piecewise linear representations is also introduced in order to quantify performance. The metric is evaluated on a wide range of low bit rate video content and shown to perform well in terms of the shape and overall mean of the output perceived quality waveform.